We systematically investigated the effects of process conditions and reduced graphene oxide (RGO) loading on the H2S gas-sensing performance of the α-Fe2O3 nanofibers (NFs) fabricated via on-chip ...electrospinning. The annealing temperature and precursor solution contents strongly influenced on the morphology and structure of the α-Fe2O3 NFs that accordingly affected on the gas-sensing performance. The optimum process conditions with the annealing temperature of 600 °C and the precursor solution contents of 11 wt% PVA and 4.0 wt% Fe(NO3)3.9H2O led to the α-Fe2O3 NF sensors having a high response of ∼6.1 at 1 ppm H2S gas. The RGO loading further improved the gas response, increasing the response to 1 ppm H2S gas up to ∼9.2. Also, the RGO-loaded α-Fe2O3 NF sensors enhanced their selectivity and detection limit as compared with pure α-Fe2O3 NF sensors. The enhanced gas-sensing performance was attributed to the presence of nanograins, the increase of surface-to-volume ratio and the formation of potential barriers at nanograin homojunctions and RGO/α-Fe2O3 heterojunctions.
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•The process conditions have been optimized for α-Fe2O3 nanofiber gas sensor.•RGO-loaded α-Fe2O4 nanofiber sensors can detect H2S gas down to ppb level.•The loading RGO-loaded α-Fe2O4 can result in enhanced H2S gas response.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
SnO2 NF sensors were fabricated on-chip using the electrospinning method as illustrate in the inset. Dynamic responses of the SnO2 NF sensors at 350 °C to various gases indicate a high sensitivity of ...the fabricated sensor to H2S gas with a good selectivty.
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•One-step fabrication of SnO2 NFs via electrospinning method was proposed.•Sensing characteristics of fabricated SnO2 NF sensor to 0.1–1 ppm H2S were studied.•Investigating dislocation defect and activation energy of the synthesized SnO2 NFs.•Gas sensing properties were explained by surface depletion/grain boundary mechanisms.
SnO2 porous nanofibers (NFs) were deposited on-chip by using a facile electrospinning method followed by heat treatment at 600 °C and used to detect H2S concentrations at sub-parts per million level. Morphological, compositional, crystal, and atomic structural properties of the as-spun and calcined SnO2 NFs were investigated by field emission electron microscopy, energy dispersive spectroscopy, X-ray diffraction, and high-resolution transmission electron microscopy, respectively. SnO2 porous NFs with an average diameter of 150 nm and consisting of many nanograins were successfully fabricated by on-chip electrospinning. The NFs were crystallized as the tetragonal structure of SnO2 with an average crystallite size and dislocation density of approximately 13.5 nm and 5.615 × 1015 lines/m2, respectively. The sensing characteristics of the SnO2 NF sensors were tested with 0.1–1 ppm H2S from 150 °C to 450 °C. The sensor achieved the optimal performance at 350 °C and exhibited gas response of 15.2 with fast response/recovery times of 15 s/230 s. The H2S gas sensing mechanisms of the SnO2 porous NF sensors were due to the modulation of the resistance along the surface depletion layer and the grain boundaries. The fabricated sensor also indicated a good selectivity to H2S, short-term stability, and the low detection limit of 1.6 ppb. The influence of humidity on the sensor’s performance in a low temperature range is also discussed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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•Facile on-chip electrospinning has been developed for preparing ZnFe2O4 nanofibers.•ZnFe2O4 nanofiber sensors can detect H2S gas down to ppb level.•Nanograin size and crystallinity ...have correlative effect on gas sensing performance.
ZnFe2O4 nanofiber gas sensors are cost-effectively fabricated by direct electrospinning on microelectrode chip with Pt interdigitated electrodes and subsequent calcination under different conditions to maximize their response to H2S gas. The synthesized nanofibers of approximately 30–100 nm in diameter show typical spider-net-like morphology of the electrospun nanofibers. The ZnFe2O4 nanofibers comprise many 10–25 nm nanograins, which results in multi-porous structures. Moreover, the nanofibers exhibit the single phase of cubic-spinel-structure ZnFe2O4. The density, crystallinity and grain size of ZnFe2O4 nanofiber that strongly affect gas-sensing properties can be optimized by controlling electrospun time, annealing temperature, annealing time and heating rate. Under optimal conditions, the ZnFe2O4 nanofiber sensors exhibit high sensitivity and selectivity to H2S at sub-ppm levels. Excellent gas-sensing performances are attributed to effects of multi-porous structure, nanograin size and crystallinity, which is explained by the sensing mechanisms of ZnFe2O4 nanofiber sensors to H2S gas.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
•An effective design has been realized for self-heated sensors using network nanowires.•The density of nanowires was optimized via controlling of the gap size of heat-to-heat electrodes.•The dense of ...network nanowires consumes a high power but is effective for detection of reducing gas.
Developing metal oxide gas sensors for internet-of-things (IoT) and portable applications require low-power consumption because of the limited battery in devices. This requirement is challenging because metal oxide sensors generally need high working temperatures, especially for reducing gases. Herein, we present an effective design and fabrication method of a SnO2 nanowire (NW) sensor for reducing gases by using the Joule heating effect at NW nanojunctions without needing an external or integrated heater. The sensor’s low-power consumption at around 4 mW was controlled by the size and nanojunction density of the device. The sensor has a simple design and is easy to fabricate. A proof-of-concept of a portable gas sensor module can be realised for monitoring highly toxic reducing gases, such as H2S, NH3 and C2H5OH, by using the developed self-heated NWs.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•Simple liquid-phase exfoliated method to fabricate few-layered MoS2 nanosheets.•Significant NO2 sensing performance of the sensor based on exfoliated MoS2 compared to that based on bulk MoS2.•The ...sensor based on the exfoliated MoS2 nanosheets indicates the highest response of about 8 times to 5 ppm at RT.•The exfoliated MoS2 nanosheet sensor shows good NO2 selectivity, ultra-low detection limit, good short- and long-term stability.
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Gas sensors based on the bulk MoS2 and exfoliated MoS2 nanosheets, were fabricated by the probe ultrasonic vibration followed by the drop-casting method. The sensing performance of the sensor based on the exfoliated MoS2 was much higher than that based on the bulk MoS2. The exfoliated MoS2 sensor showed highest gas response of approximately eight times to 5 ppm NO2 at room temperature. This fabricated sensor showed a good NO2 selectivity, ultra-low detection limit, and good short- and long-term stability.
Features such as surface-to-volume ratio, sensitive surface, and bandgap vary with the number of material layers of semiconductor two-dimensional transition metal dichalcogenides with superior responsivity at room temperature (RT) and their possible application as flexible electronic devices. Herein, a significant enhancement of NO2 gas sensing properties of few-layered MoS2 nanosheets exfoliated from bulk MoS2 through a simple sonication probe was reported. The gas responses of the sensor based on the exfoliated MoS2 nanosheets to 0.5–5 ppm NO2 at RT were as high as 5.3–8 times. At RT, the humidity effect to the performance of the exfoliated MoS2 sensor was insignificant. The exfoliated MoS2 sensor also exhibited an ultra-low detection limit of 27 ppb, excellent selectivity, and reliable long-term stability within 8 weeks, which are crucial for future application of the sensor in practical devices. The NO2 sensing mechanism of the exfoliated MoS2 nanosheets was discussed in detail.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The selective detection and classification of NH3 and H2S gases with H2S gas interference based on conventional SnO2 thin film sensors is still the main problem. In this work, three layers of ...SnO2/Pt/WO3 nanofilms with different WO3 thicknesses (50, 80, 140, and 260 nm) were fabricated using the sputtering technique. The WO3 top layer were used as a gas filter to further improve the selectivity of sensors. The effect of WO3 thickness on the (NH3, H2, and H2S) gas-sensing properties of the sensors was investigated. At the optimal WO3 thickness of 140 nm, the gas responses of SnO2/Pt/WO3 sensors toward NH3 and H2 gases were slightly lower than those of Pt/SnO2 sensor film, and the gas response of SnO2/Pt/WO3 sensor films to H2S gas was almost negligible. The calcification of NH3 and H2 gases was effectively conducted by machine learning algorithms. These evidences manifested that SnO2/Pt/WO3 sensor films are suitable for the actual NH3 detection of NH3 and H2S gases.
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•The three layers of the SnO2/Pt/WO3 nanofilms based-gas sensor have been developed.•The SnO2/Pt/WO3 nanofilms can detect NH3 and H2 gases at low concentrations.•The classification of NH3 and H2 gases is made by machine learning algorithms.•The cross-response of sensors to interfering gas such as H2S were almost eliminated.•The gas filter mechanism was explained by the molecular size of the tested gases.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The monitoring and classification of different gases, such as H2 and NH3 using a low-cost resistive semiconductor sensor is preferred in practical applications in hydrogen energy, breath analysis, ...air pollution monitoring, industrial control, and etc. Herein, porous bi-layer Pt/SnO2 thin film sensors were fabricated to enhance H2 and NH3 sensing performance for effective monitoring and classification. Different Pt film thicknesses of 2, 5, 10, and 20 nm were deposited on 150 nm SnO2 film-based sensors by sputtering method to optimize the response to H2 and NH3 gases. Gas sensing results showed that the fabricated Pt/SnO2 films significantly improved the sensor response to NH3 and H2 compared to pure SnO2 thin film. The sensors based on 5 and 10 nm Pt catalyst layers presented the highest responses to H2 and NH3, respectively. The optimal working temperature for NH3 was in the range from 250 °C to 350 °C, and that for H2 gas is less than 200 °C. The response of Pt/SnO2 sensors to CH4, CO, H2S, and liquefied petroleum gas was much lower than that to NH3 and H2 supporting the high selectivity. On the basis of sensing results at different working temperatures or Pt thicknesses, we applied a radar plot and linear discriminant analysis methods to distinguish NH3 and H2. The results showed that H2 and NH3 could be classified without any confusion with different Pt layer thicknesses at a working temperature of 250 °C.
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•Pt/SnO2 bilayer thin film sensor showed excellent response to H2 and NH3.•The optimal Pt layer thicknesses were different for H2 and NH3 gases.•Gas classification is realized by changing working temperature and Pt thickness.•Turning the Pt thickness is better than temperature gradient for gas classification.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•Heterojunctions of rGO and ZnO nanofibers exhibited ultrasensitive H2S gas sensing.•The effects of external and internal junctions on H2S gas-sensing were studied.•The cross-response of the ...heterojunction sensors to other reducing gases were almost eliminated.•A novel sulfuration-desulfuration sensing mechanism is proposed.
External and internal heterojunctions of reduced graphene oxide (rGO) and ZnO nanofibers (NFs) are developed for ultrasensitive H2S sensing. The gas response of both heterojunctions is significantly higher than that of bare ZnO NFs. The internal heterojunction of 0.1 wt% rGO/ZnO NFs exhibited the highest gas response, reaching 1353–1 ppm H2S at 350 °C and increasing up to 25-fold, compared to bare ZnO NFs. Whereas response of the former to 1000 ppm H2, 1000 ppm NH3, and 1 ppm SO2 gases is negligible (1.5–9). Moreover, the present sensor exhibits an ultralow detection limit of 4.9 ppt and excellent stability towards H2S. A novel sulfuration-desulfuration sensing mechanism is proposed to explain the high response and selectivity to H2S.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Dengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a ...prioritised health adaptation measure to climate change in Vietnam.
This study aimed to develop an accurate DF prediction model in Vietnam using a wide range of meteorological factors as inputs to inform public health responses for outbreak prevention in the context of future climate change.
Convolutional neural network (CNN), Transformer, long short-term memory (LSTM), and attention-enhanced LSTM (LSTM-ATT) models were compared with traditional machine learning models on weather-based DF forecasting. Models were developed using lagged DF incidence and meteorological variables (measures of temperature, humidity, rainfall, evaporation, and sunshine hours) as inputs for 20 provinces throughout Vietnam. Data from 1997-2013 were used to train models, which were then evaluated using data from 2014-2016 by Root Mean Square Error (RMSE) and Mean Absolute Error (MAE).
LSTM-ATT displayed the highest performance, scoring average places of 1.60 for RMSE-based ranking and 1.95 for MAE-based ranking. Notably, it was able to forecast DF incidence better than LSTM in 13 or 14 out of 20 provinces for MAE or RMSE, respectively. Moreover, LSTM-ATT was able to accurately predict DF incidence and outbreak months up to 3 months ahead, though performance dropped slightly compared to short-term forecasts. To the best of our knowledge, this is the first time deep learning methods have been employed for the prediction of both long- and short-term DF incidence and outbreaks in Vietnam using unique, rich meteorological features.
This study demonstrates the usefulness of deep learning models for meteorological factor-based DF forecasting. LSTM-ATT should be further explored for mitigation strategies against DF and other climate-sensitive diseases in the coming years.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Gas sensors based on Au doped ZnO/SnO2 NFs were fabricated by the electrospinning method (on the right). The sensor based on the 0.005 wt.% Au doped ZnO/SnO2 NFs shows highest H2S gas sensitivity ...compared to other gases (on the left). This confirms the good H2S gas selectivity of the fabricated sensor.
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•On-chip fabrication of Au doped ZnO/SnO2-based sensors via electrospinning method•Investigation of sensing characteristics of fabricated Au doped ZnO/SnO2 NF sensor to 0.1–1 ppm H2S•Finding the optimal Au doping concentration into ZnO/SnO2 composite NFs to enhance H2S gas sensing characteristics.•Gas sensing mechanism of the Au doped ZnO/SnO2 NFs were explained.
Nanofibers of ZnO-SnO2 nanocomposites doped with Au crystals were synthesized by an electrospinning method for enhancement of H2S gas sensing performance. The mixed solution of zinc acetate dihydrate and tin(II) chloride dihydrate, dissolved in ethanol/DMF solvent, was spun directly on the interdigital Pt electrodes for sensor fabrication. Thermal treatment was carried out to convert the spun nanofibers into ZnO-SnO2 nanocomposites doped with Au crystals. SEM and TEM observation confirmed the formation of porous nanofibers with an average diameter of about 120 nm. X-ray diffraction studies revealed that the nanocomposites of ZnO and SnO2 phases were formed, but not ZnSnO3, despite the precursor solution being mixed on the atomic scale from the starting solution. Doping with 0.001, 0.005 and 0.01 wt.% of Au slightly changed the morphology of the nanofibers because the Au was not doped into the crystals of ZnO or SnO2, but mostly existed as the surface decoration. This ensured that the effective surface catalyzed the gas reaction, thus enhance the sensing performance. Gas sensitivity to H2S gas was improved by approximately 700% with the optimal doping concentration of Au.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP